# LitmusChaos — Cloud-Native Chaos Engineering for Kubernetes

> Inject controlled failures into your Kubernetes workloads to test resilience. A CNCF incubating project with a library of 50+ chaos experiments.

## Install

Save as a script file and run:

# LitmusChaos — Cloud-Native Chaos Engineering for Kubernetes

## Quick Use
```bash
helm repo add litmuschaos https://litmuschaos.github.io/litmus-helm
helm install litmus litmuschaos/litmus 
  --namespace litmus --create-namespace
# Access the ChaosCenter dashboard:
kubectl -n litmus get svc litmusportal-frontend-service
```

## Introduction
LitmusChaos is a CNCF incubating project that brings chaos engineering to Kubernetes. It provides a framework for running controlled failure experiments, pod kills, network delays, CPU stress, and more, so teams can verify that their applications recover gracefully under adverse conditions.

## What LitmusChaos Does
- Runs chaos experiments as Kubernetes CRDs with a declarative YAML workflow
- Offers a ChaosHub with 50+ prebuilt experiments for pods, nodes, and infrastructure
- Provides a web-based ChaosCenter for designing, scheduling, and observing experiments
- Supports steady-state hypothesis checks to validate resilience automatically
- Integrates with CI/CD pipelines to run chaos tests as part of deployment validation

## Architecture Overview
LitmusChaos consists of a control plane (ChaosCenter) and an execution plane. ChaosCenter is a web application backed by MongoDB that manages experiment definitions and schedules. The execution plane runs in each target cluster as a set of operators: the Chaos Operator watches ChaosEngine CRDs and launches experiment pods that inject the specified failure. Results are reported back to ChaosCenter for analysis and visualization.

## Self-Hosting & Configuration
- Deploy ChaosCenter via Helm chart or kubectl manifests into a management cluster
- Register target clusters as Chaos Delegates through the ChaosCenter UI
- Browse the ChaosHub to select and customize experiments
- Define ChaosWorkflows combining multiple experiments with steady-state checks
- Schedule recurring chaos tests via cron expressions in the workflow definition

## Key Features
- CNCF incubating project with an active community and vendor-neutral governance
- 50+ prebuilt experiments covering pod, node, network, DNS, and cloud provider faults
- GitOps-native experiment management with version-controlled workflow definitions
- Observability integration with Prometheus metrics and Grafana dashboards
- Multi-cluster chaos orchestration from a single ChaosCenter instance

## Comparison with Similar Tools
- **Chaos Mesh** — CNCF project with similar Kubernetes-native chaos; LitmusChaos offers a richer web UI and ChaosHub marketplace
- **Gremlin** — Commercial SaaS chaos platform; LitmusChaos is fully open-source and self-hosted
- **AWS Fault Injection Simulator** — AWS-only managed service; LitmusChaos works on any Kubernetes cluster
- **Pumba** — Docker-level chaos tool; LitmusChaos operates at the Kubernetes abstraction layer with CRD-driven workflows

## FAQ
**Q: Can LitmusChaos cause production outages?**
A: Experiments are scoped by namespace, labels, and blast radius controls. Start with non-production clusters and narrow targeting to reduce risk.

**Q: Does it require ChaosCenter to run experiments?**
A: No. You can run experiments directly via ChaosEngine CRDs and kubectl without ChaosCenter, though the UI simplifies workflow management.

**Q: How do I create a custom chaos experiment?**
A: Write a Go or shell-based experiment, package it as a container image, and register it in a custom ChaosHub or inline in your workflow.

**Q: What steady-state hypothesis checks are supported?**
A: Built-in probes support HTTP endpoints, command output, Kubernetes resource conditions, and Prometheus queries.

## Sources
- https://github.com/litmuschaos/litmus
- https://docs.litmuschaos.io

---
Source: https://tokrepo.com/en/workflows/e0fe8444-3974-11f1-9bc6-00163e2b0d79
Author: Script Depot